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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article ESVD: An Integrated Energy Scalable Framework for Low-Power Video Decoding Systems | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2010 Article ID 234131 14 pages doi 10.1155 2010 234131 Research Article ESVD An Integrated Energy Scalable Framework for Low-Power Video Decoding Systems Wen Ji 1 Min Chen 2 Xiaohu Ge 3 Peng Li 1 and Yiqiang Chen1 1 Institute of Computing Technology CAS Beijing 100190 China 2 Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada V6T1Z4 3 Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan Hubei 234131 China Correspondence should be addressed to Xiaohu Ge xhge@mail.hust.edu.cn Received 1 April 2010 Accepted 6 June 2010 Academic Editor Liang Zhou Copyright 2010 Wen Ji et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Video applications using mobile wireless devices are a challenging task due to the limited capacity of batteries. The higher complex functionality of video decoding needs high resource requirements. Thus power efficient control has become more critical design with devices integrating complex video processing techniques. Previous works on power efficient control in video decoding systems often aim at the low complexity design and not explicitly consider the scalable impact of subfunctions in decoding process and seldom consider the relationship with the features of compressed video date. This paper is dedicated to developing an energy-scalable video decoding ESVD strategy for energy-limited mobile terminals. First ESVE can dynamically adapt the variable energy resources due to the device aware technique. Second ESVD combines the decoder control with decoded data through classifying the data into different partition profiles according to its characteristics. Third it introduces utility theoretical
